Philips Speech Recognition Systems of Vienna, Austria, has signed a deal to integrate its SpeechMagic technology into application software from VoiceViewer Technologies of Bannockburn, IL.
The partnership will support the capture of patient information at the point of care, and will consist of a new wireless, handheld device that will allow nursing staff to enter information into their systems by voice.
VoiceViewer features a preloaded checklist that helps nurses record all vital patient data, such as respiratory or behavior patterns, according to Philips.
Related Reading
Road to RSNA, Speech Recognition & Recording, Philips Speech Recognition Systems, October 31, 2007
Philips' Australian SR installation shows positive results, August 21, 2007
Philips completes U.K. installation, August 15, 2008
Philips brings SpeechMagic to Sint-Jan, August 7, 2007
Philips SpeechMagic receives Citrix Ready status, June 21, 2007
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![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
